共查询到20条相似文献，搜索用时 546 毫秒
1.
Multiobjective optimization deals with mathematical optimization problems where two or more objective functions (cost functions) are to be optimized (maximized or minimized) simultaneously. In most cases of interest, the objective functions are in conflict, i.e., there does not exist a decision (design) vector (vector of optimization variables) at which every objective function takes on its optimal value. The solution of a multiobjective problem is commonly defined as a Pareto front, and any decision vector which maps to a point on the Pareto front is said to be Pareto optimal. We present an original derivation of an analytical expression for the steepest descent direction for multiobjective optimization for the case of two objectives. This leads to an algorithm which can be applied to obtain Pareto optimal points or, equivalently, points on the Pareto front when the problem is the minimization of two conflicting objectives. The method is in effect a generalization of the steepest descent algorithm for minimizing a single objective function. The steepest-descent multiobjective optimization algorithm is applied to obtain optimal well controls for two example problems where the two conflicting objectives are the maximization of the life-cycle (long-term) net-present-value (NPV) and the maximization of the short-term NPV. The results strongly suggest the multiobjective steepest-descent (MOSD) algorithm is more efficient than competing multiobjective optimization algorithms. 相似文献
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R. M. Fonseca O. Leeuwenburgh P. M. J. Van den Hof J. D. Jansen 《Computational Geosciences》2014,18(3-4):449-461
In an earlier study, two hierarchical multi-objective methods were suggested to include short-term targets in life-cycle production optimization. However, this earlier study has two limitations: (1) the adjoint formulation is used to obtain gradient information, requiring simulator source code access and an extensive implementation effort, and (2) one of the two proposed methods relies on the Hessian matrix which is obtained by a computationally expensive method. In order to overcome the first of these limitations, we used ensemble-based optimization (EnOpt). EnOpt does not require source code access and is relatively easy to implement. To address the second limitation, we used the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm to obtain an approximation of the Hessian matrix. We performed experiments in which water flood was optimized in a geologically realistic multilayer sector model. The controls were inflow control valve settings at predefined time intervals. Undiscounted net present value (NPV) and highly discounted NPV were the long-term and short-term objective functions used. We obtained an increase of approximately 14 % in the secondary objective for a decrease of only 0.2–0.5 % in the primary objective. The study demonstrates that ensemble-based hierarchical multi-objective optimization can achieve results of practical value in a computationally efficient manner. 相似文献
4.
Huiming Tang Wenping Gong Liangqing Wang C. Hsein Juang James R. Martin Changdong Li 《国际地质力学数值与分析法杂志》2019,43(7):1516-1536
Though the technology of using stabilizing piles to prevent landsliding is not new, the design of such piles with a meaningful optimization framework has been rarely reported. In this paper, a multiobjective optimization-based framework for design of stabilizing piles is presented, in which both reinforcement effectiveness and cost efficiency could be explicitly considered. The design parameters considered in the proposed design framework are the pile parameters, including pile diameter, spacing, length, and position, and the design objectives considered are the reinforcement effectiveness and cost efficiency. The design of stabilizing piles is then implemented as a multiobjective optimization problem. In that the desire to maximize the reinforcement effectiveness and that to maximize the cost efficiency are two conflicting objectives, the output of this multiobjective optimization will be a Pareto front that depicts a trade-off between these two design objectives. With the obtained Pareto front, an informed decision regarding the design of stabilizing piles is reached. The effectiveness and significance of the proposed multiobjective optimization-based design framework for stabilizing piles are demonstrated through two illustrative examples: one is the design of stabilizing piles in a one-layer earth slope and the other the design of stabilizing piles in a two-layer earth slope. Further, parametric analyses are conducted to investigate the influences of the pile design parameters on the stability of reinforced slopes. 相似文献
5.
Optimal design of groundwater remediation systems using a multi-objective fast harmony search algorithm 总被引：1，自引：0，他引：1
A new multi-objective optimization methodology is developed, whereby a multi-objective fast harmony search (MOFHS) is coupled with a groundwater flow and transport model to search for optimal design of groundwater remediation systems under general hydrogeological conditions. The MOFHS incorporates the niche technique into the previously improved fast harmony search and is enhanced by adding the Pareto solution set filter and an elite individual preservation strategy to guarantee uniformity and integrity of the Pareto front of multi-objective optimization problems. Also, the operation library of individual fitness is introduced to improve calculation speed. Moreover, the MOFHS is coupled with the commonly used flow and transport codes MODFLOW and MT3DMS, to search for optimal design of pump-and-treat systems, aiming at minimization of the remediation cost and minimization of the mass remaining in aquifers. Compared with three existing multi-objective optimization methods, including the improved niched Pareto genetic algorithm (INPGA), the non-dominated sorting genetic algorithm II (NSGAII), and the multi-objective harmony search (MOHS), the proposed methodology then demonstrated its applicability and efficiency through a two-dimensional hypothetical test problem and a three-dimensional field problem in Indiana (USA). 相似文献
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以发电量和保证出力为目标建立梯级水电站的多目标发电优化调度模型,对三峡梯级中长期发电优化调度进行研究。针对传统方法求解多目标优化问题的局限,提出一种强度Pareto差分进化算法(Strength Pareto Differential Evolution,SPDE)用于求解梯级水电站的多目标发电优化调度问题。SPDE以差分进化算法(Differential Evolution,DE)为基础,采用SPEA2的适应度评价方法,并根据多目标优化的特点对DE的进化算子进行修正。同时,提出一种自适应柯西变异策略(Adaptive Cauchy Mutation,ACM)用于克服算法的早熟收敛问题。三峡梯级水电站实例研究结果表明,SPDE可同时考虑两个目标并有效处理复杂约束条件,一次运行即可得到一组在各目标分布均匀、分布范围广的非劣调度方案供决策者评价优选。 相似文献
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Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum
resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both
methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated
method uses a plot of field size versus size rank, and (2) the log–geometric method uses data binned in field-size classes
and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions
from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates
of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log–geometric methods, generally
stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can
vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger
than those of the log–geometric method where the number of discovered pools is more than 100. Both methods, however, tend
to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by
sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show
how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency
gives better estimates of the Pareto shape parameters. 相似文献
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随着城市建设的发展，渣土边坡的数量和规模急剧增加，渣土边坡的防控研究受到了广泛关注。针对渣土边坡人工分层堆填建筑余渣土体参数的不确定性，采用预埋阻滑键加固渣土边坡的方式，提出了基于可靠度理论的阻滑键多目标优化设计方法。考虑不同阻滑键潜在组合对渣土边坡预估破坏损失的影响，将渣土边坡的预估破坏损失、稳定安全性和加固设计成本作为设计目标，通过多目标优化理论确定帕累托前沿并计算其关节点，获得预埋阻滑键加固边坡的最佳设计方案。以深圳市某渣土边坡为例，计算结果表明，将破坏概率作为衡量阻滑键加固渣土边坡效果指标时，应在渣土边坡前缘预埋两组尺寸长3 m、间距5 m的阻滑键加固边坡。采用上述阻滑键设计组合加固该渣土边坡时，可实现该边坡预估破坏损失、设计成本和稳定性达到最佳平衡。 相似文献
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应用油田开发区岩心、测井及地震等资料,对胜坨油田二区7砂组高分辨率层序发育特征以及不同级次基准面旋回内部沉积微相空间展布规律进行研究。研究表明,该区7砂组发育多级基准面旋回,包括1个长期基准面旋回、2个中期基准面旋回和9个短期基准面旋回,反映了可容空间与沉积物补给速率比值(A/S比值)在纵向上的多级变化发育模式,即在A/S比值总体向上变小的背景上,有多个次级A/S比值向上变小再变大的旋回。随着基准面的下降-波动-下降,沉积微相从7砂组底部的河口坝过度为地层中部的席状砂背景下残存的分流河道沉积,再到7砂组上部的河口坝沉积。A/S比值控制着研究区沉积微相的发育类型、展布模式。弄清楚研究区地层沉积特征与基准面旋回之间的关系对于精细储层表征和油田开发中后期井网调整具有重要指导意义。 相似文献
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This paper treats the upscaling of the absolute permeability in a heterogeneous reservoir. By replacing the fine scale permeability tensor with an upscaled, or effective permeability tensor, a modelling error is introduced. An a posteriori error estimate on this modelling error is formulated and tested. An implementation of the theory, based on domain decomposition coupled with a hierarchical representation of the absolute permeability field, is given. As hierarchical basis functions we have chosen the Haar system, which leads to a wavelet representation of the permeability. The wavelet representation offers a natural upscaling technique which resembles the highcut filters commonly used in signal analysis. This procedure represents an adaptive upscaling method. The numerical results show that this method conserves both the dissipation and the mean velocity in the problem fairly well. The a posteriori error estimate on the modelling error coupled with domain decomposition methods constitutes a powerful modelling tool. 相似文献
11.
Accurate prediction of settlement for shallow footings on cohesionless soil is a complex geotechnical problem due to large uncertainties associated with soil. Prediction of the settlement of shallow footings on cohesionless soil is based on in situ tests as it is difficult to find out the properties of soil in the laboratory and standard penetration test (SPT) is the most often used in situ test. In data driven modelling, it is very difficult to choose the optimal input parameters, which will govern the model efficiency along with a better generalization. Feature subset selection involves minimization of both prediction error and the number of features, which are in general mutual conflicting objectives. In this study, a multi-objective optimization technique is used, where a non-dominated sorting genetic algorithm (NSGA II) is combined with a learning algorithm (neural network) to develop a prediction model based on SPT data based on the Pareto optimal front. Pareto optimal front gives the user freedom to choose a model in terms of accuracy and model complexity. It is also shown how NSGA II can be effectively applied to select the optimal parameters and besides minimizing the error rate. The developed model is compared with existing models in terms of different statistical criteria and found to be more efficient. 相似文献
12.
传统多目标决策方法难以刻画流域水资源系统调度周期内多目标互馈关系及需求动态变化, 可能导致关键时期特定目标保障不足。为弥补该缺陷, 提出多目标时变偏好决策方法。以金沙江下游为例, 分析发电与生态目标需求的时空变异性, 构建并求解两目标随时程变化的Pareto前沿簇, 量化各时期目标间竞争强度, 基于灵敏比的非支配关系, 定量识别各调度时期决策人的目标偏好, 形成偏向度决策支持集, 建立多目标时变决策模型。结果表明: 考虑时变偏好的决策方法, 其动态累积Pareto前沿可以支配传统静态Pareto前沿; 相较于传统方法, 研究区全年增发电量0.7亿kW·h, 全年和关键生态期生态效益分别提升8.06%和2.83%, 可以在保持发电效益的同时显著优化生态效益, 并提高关键时期生态需求的保障程度。 相似文献
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通过对延长油田郭旗西区长6油层组储层的沉积微相、储层的岩石学特征、成岩作用、孔隙结构特征和物性条件研究，探讨了影响储集条件和油气成藏的主要因素.延长油田郭旗西区三叠系延长组长6早期沉积微相以三角洲前缘水下分流河道为主，长6晚期以三角洲平原分流河道沉积为主，储集层发育.受成岩后生作用影响，形成了低孔隙度、特低-超低渗透率的储集层.油藏分布主要受沉积微相和储层物性控制，为典型的岩性油藏。 相似文献
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为实现滨海含水层地下水开采-回灌方案优化、控制海水入侵面积和降低海水入侵损失等多重管理目标,建立了海水入侵条件下地下水多目标模拟优化管理模型SWT-NPTSGA。模拟模型采用基于变密度流的数值模拟程序SEAWAT来模拟海水入侵过程。优化模型采用小生境Pareto禁忌遗传混合算法NPTSGA来求解,该算法在保证多目标权衡解的收敛性和计算效率的前提下,能维护整个进化群体的全局多样性。将SWT-NPTSGA程序应用于一个理想滨海含水层地下水开采方案和人工回灌控制海水入侵的优化设计中,结果表明该管理模型能够同时处理最大化总抽水流量、最小化人工回灌总量和最小化海水入侵范围等3个目标函数之间的权衡关系。通过采用人工回灌海水入侵区的减灾策略,既能增加滨海地区的供水量,又可减少海水入侵的范围,由此进一步验证了模型的有效性和可靠性。 相似文献
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In the development of naturally fractured reservoirs (NFRs), the existence of natural fractures induces severe fingering and breakthrough. To manage the flooding process and improve the ultimate recovery, we propose a numerical workflow to generate optimal production schedules for smart wells, in which the inflow control valve (ICV) settings can be controlled individually. To properly consider the uncertainty introduced by randomly distributed natural fractures, the robust optimization would require a large ensemble size and it would be computationally demanding. In this work, a hierarchical clustering method is proposed to select representative models for the robust optimization in order to avoid redundant simulation runs and improve the efficiency of the robust optimization. By reducing the full ensemble of models into a small subset ensemble, the efficiency of the robust optimization algorithm is significantly improved. The robust optimization is performed using the StoSAG scheme to find the optimal well controls that maximize the net-present-value (NPV) of the NFR’s development. Due to the discrete property of a natural fracture field, traditional feature extraction methods such as model-parameter-based clustering may not be directly applicable. Therefore, two different kinds of clustering-based optimization methods, a state-based (e.g., s w profiles) clustering and a response-based (e.g., production rates) clustering, are proposed and compared. The computational results show that the robust clustering optimization could increase the computational efficiency significantly without sacrificing much expected NPV of the robust optimization. Moreover, the performance of different clustering algorithms varies widely in correspondence to different selections of clustering features. By properly extracting model features, the clustered subset could adequately represent the uncertainty of the full ensemble. 相似文献
16.
长江上游水资源耦合系统优化调控涉及供水、发电和生态需水等相互竞争、不可公度的调控目标。其供水-发电-环境互馈协变机制难以数学解析和刻画，多维目标效益均衡优化调控难以实施。为此，以多目标优化、运筹学理论及方法为基础，提出了基于梯度分析法的供水-发电-环境两两互馈关系研究方法。通过多目标约束优化方法求解长江上游水库群联合优化调度在供水-发电-环境目标空间的最优解集，并进行插值构造了供水-发电-环境互馈关系多维空间曲面，以此为基础，采用一阶差分近似求解供水对环境和发电对环境偏导函数值，以量化环境对供水变化和发电变化响应的梯度，进而解析环境-供水和环境-发电间互馈协变关系。该方法为水库群优化调度多目标互馈关系研究提供了一种新的思路。 相似文献
17.
长江上游水资源耦合系统优化调控涉及供水、发电和生态需水等相互竞争、不可公度的调控目标。其供水-发电-环境互馈协变机制难以数学解析和刻画，多维目标效益均衡优化调控难以实施。为此，以多目标优化、运筹学理论及方法为基础，提出了基于梯度分析法的供水-发电-环境两两互馈关系研究方法。通过多目标约束优化方法求解长江上游水库群联合优化调度在供水-发电-环境目标空间的最优解集，并进行插值构造了供水-发电-环境互馈关系多维空间曲面，以此为基础，采用一阶差分近似求解供水对环境和发电对环境偏导函数值，以量化环境对供水变化和发电变化响应的梯度，进而解析环境-供水和环境-发电间互馈协变关系。该方法为水库群优化调度多目标互馈关系研究提供了一种新的思路。 相似文献
18.
Yun Yang Jianfeng Wu Xiaomin Sun Jichun Wu Chunmiao Zheng 《Environmental Earth Sciences》2013,70(6):2481-2494
Two primary goals of a multi-objective evolutionary algorithm (MOEA) for solving multi-objective optimization problems are to find as many nondominated solutions as possible toward the true Pareto front and to maintain diversity of Pareto-optimal solutions along the tradeoff curves. However, few MOEAs can achieve these two goals concurrently. This study presents a new hybrid MOEA, the niched Pareto tabu search combined with a genetic algorithm (NPTSGA), in which the global search ability of niched Pareto tabu search (NPTS) is improved by the diversification of candidate solutions that arose from the evolving population of nondominated sorting genetic algorithm-II (NSGA-II). The NPTSGA coupled with a flow and transport model is developed for multi-objective optimal design of groundwater remediation systems. The proposed methodology is then applied to a large field-scale groundwater remediation system for cleanup of large trichloroethylene plume at the Massachusetts Military Reservation in Cape Cod, Massachusetts. Furthermore, a master-slave (MS) parallelization scheme based on the Message Passing Interface is incorporated into the NPTSGA to implement objective function evaluations in a distributed processor environment, which can greatly improve the efficiency of the NPTSGA in finding Pareto-optimal solutions to the real-world applications. This study shows that the MS parallel NPTSGA in comparison with the original NPTS and NSGA-II can balance the tradeoff between the diversity and optimality of solutions during the search process and is an efficient and effective tool for optimizing the multi-objective design of groundwater remediation systems under complicated hydrogeologic conditions. 相似文献
19.
油田开发后期提液井优选的地质条件 总被引：1，自引：0，他引：1
老井放大生产压差进行有效提液是提高注采系统排液能力的一种重要途径。分析了双河油田储层主要微相砂体的产液和吸水能力,认为油田开发后期前缘席状砂提液能力差,而水下分流河道和河口坝具有较强的提液能力;油田开发后期前缘席状砂吸水能力差,难以补充提液后造成油层压力亏空,而水下分流河道和河口坝具有较强的吸水能力,很容易实现注采平衡,保证油井持续提液。同时,从新井钻遇状况、数值模拟和单井水驱曲线分析了油田开发后期剩余油分布状况,认为能用水动力学方法开采的剩余油主要富集在水下分流河道中。因此,双河油田在油田开发后期的提液井应选择在水下分流河道微相砂体的油井中。实践结果也表明,选择在水下分流河道砂体的油井中放压提液能取得较好的稳油控水效果。 相似文献
20.
安塞油田王窑地区长6油层沉积微相研究 总被引：16，自引：4，他引：16
王窑地区长6油层为湖泊河控三角洲前缘沉积。主要沉积微相为三角洲前缘水下分流河道、分流河口砂坝、前缘砂席和分流间等。水下分流河道充填沉积为向上变细的砂岩层序，分流河口砂坝可期分为向上变粗的前积式和非前积式两种沉积层序类型。水下分流河道和河口砂坝砂体相互连接，形成厚度较稳定的三角洲前缘复合体。该区三角洲沉积是安塞三角洲发育较晚的一支，也是指状砂体仲入湖区最远、发育程度最高的分支。长61^1沉积期。为三角洲的初始进积阶段。三角洲沉积由两支分流组成。长61^2沉积期三角洲前缘体系完整，砂体发育，分流带相互叠置交错。根据岩心描述结果，结合砂体形态和连井剖面对比分析，对长6油层三角洲沉积微相进行了综合表征。并提出了开发调整意见，为王窑地区特低渗透油田的高效开发奠定了地质基础。 相似文献